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Record W2031934661 · doi:10.1063/1.2752169

Relaxation during polymerization on slow heating and the vibrational heat capacity of the polymers

2007· article· en· W2031934661 on OpenAlexaff
C. Ferrari, E. Tombari, G. Salvetti, G. P. Johari

Bibliographic record

VenueThe Journal of Chemical Physics · 2007
Typearticle
Languageen
FieldMaterials Science
TopicMaterial Dynamics and Properties
Canadian institutionsMcMaster University
FundersCentre National de la Recherche Scientifique
KeywordsPolymerizationHeat capacityThermodynamicsPolymer chemistryRelaxation (psychology)Glass transitionPolymerChemistryMaterials scienceAnalytical Chemistry (journal)Organic chemistry

Abstract

fetched live from OpenAlex

The real and imaginary components of the complex heat capacity, C(p) (') and C(p) ("), and C(p,app) have been measured in real time during the linear chain polymerization on 12 K/h heating of six different (partially) polymerized states of a stoichiometric mixture of cyclohexylamine and diglycidyl ether of bisphenol A. Their C(p,app) shows a sigmoid shape rise with different onset temperatures T(onset), which is followed by a deep exotherm as the viscosity decreases and further polymerization occurs at different rates. The rates of their enthalpy decrease on polymerization determined by subtracting C(p) (') from C(p,app) differ but C(p) (') and C(p,app) of their final states are the same. The relaxation time increases with polymerization and decreases with an increase in T. C(p) (') rises in a sigmoid shape manner, and C(p) (") shows a peak when the relaxation time of the polymerized state is equal to the inverse of the temperature modulation frequency, whether polymerization occurs or not. The unrelaxed or vibrational heat capacity C(p,vib) of the polymers at T>T(onset) is close to C(p) of their glassy state at T<T(onset), showing that C(p) difference between the equilibrium liquid and its glass is mostly configurational. This contradicts a calculation showing that C(p,vib) change of a polymer at T(g) is generally approximately 20% of the total C(p) change.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.106

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.202
Teacher spread0.192 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2007
Admission routes1
Has abstractyes

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